Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "108"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 108 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 25 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 25 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 108, Node N09:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460008 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 14.416774 52.233314 14.222627 1.618064 6.629123 3.165025 4.750974 2.725348 0.0369 0.3591 0.1876 nan nan
2460007 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.701005 40.302564 11.117206 1.511384 5.907180 3.698566 2.501799 1.508797 0.0348 0.3277 0.1801 nan nan
2459999 RF_maintenance 0.00% 100.00% 97.33% 0.00% - - nan nan nan nan nan nan nan nan 0.0292 0.0990 0.0381 nan nan
2459998 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 9.058365 36.557096 9.505862 1.044969 7.924054 3.542085 1.677353 2.230131 0.0336 0.2909 0.1579 nan nan
2459997 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 9.930909 39.812838 10.077950 1.179237 7.675892 3.665477 3.617754 3.860061 0.0358 0.2968 0.1603 nan nan
2459996 RF_maintenance 100.00% 99.30% 99.30% 0.00% - - nan nan inf inf nan nan nan nan 0.4658 0.3693 0.2266 nan nan
2459995 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 11.276149 43.608947 11.747069 1.268344 7.992844 2.900074 1.049351 4.659656 0.0390 0.2958 0.1663 nan nan
2459994 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.792701 42.566793 10.139645 1.300625 7.745029 3.525234 0.903349 5.625566 0.0338 0.2912 0.1662 nan nan
2459993 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 11.948281 44.051789 9.421633 1.051017 10.161838 5.622477 1.288991 2.157269 0.0294 0.2417 0.1302 nan nan
2459991 RF_maintenance 100.00% 100.00% 0.11% 0.00% - - 12.788336 49.358268 9.984651 1.181519 9.169805 4.327720 0.853244 7.546179 0.0330 0.2816 0.1547 nan nan
2459990 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.338062 39.984857 9.776372 1.076982 9.064756 4.497040 0.828594 3.276152 0.0357 0.2811 0.1543 nan nan
2459989 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.099146 41.529950 8.701203 1.173350 7.989035 3.732639 0.481841 2.502827 0.0328 0.2809 0.1557 nan nan
2459988 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 12.166934 48.562625 10.087288 0.943454 10.763651 5.457371 0.735189 1.421041 0.0325 0.2901 0.1635 nan nan
2459987 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.025405 40.613472 9.784654 1.126931 6.387764 3.097431 1.855988 2.352122 0.0349 0.2940 0.1620 nan nan
2459986 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 12.539939 49.291417 10.715619 1.112814 9.361911 4.396200 5.862567 6.351336 0.0341 0.3263 0.1783 nan nan
2459985 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 11.525893 45.913178 9.929228 1.041365 7.215492 3.372369 2.105896 2.586017 0.0340 0.2845 0.1620 nan nan
2459984 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.994953 44.958909 10.298232 1.156448 9.456326 6.923939 2.981381 2.082549 0.0357 0.3073 0.1709 nan nan
2459983 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.705542 43.357569 9.857574 1.021079 9.282236 4.850784 3.275835 4.561486 0.0356 0.3372 0.1857 nan nan
2459982 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 9.294123 32.619442 8.356958 1.460984 4.522754 2.706285 2.443456 1.732283 0.0342 0.3811 0.1954 nan nan
2459981 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 9.975201 39.578341 10.507286 1.084610 10.447330 5.427580 0.917856 6.561492 0.0365 0.2829 0.1581 nan nan
2459980 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 9.777541 36.467530 9.441811 0.803848 9.027560 4.342896 5.275372 4.211356 0.0356 0.3393 0.1718 nan nan
2459979 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.175792 40.495929 8.745526 0.903922 8.940644 4.277334 0.819913 11.842813 0.0360 0.2777 0.1609 nan nan
2459978 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.274279 41.850393 9.498020 0.885222 9.330661 4.720671 0.813642 14.270272 0.0322 0.2774 0.1608 nan nan
2459977 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.579775 41.863525 9.329338 1.070474 9.242066 7.425869 1.043007 13.869883 0.0373 0.2776 0.1521 nan nan
2459976 RF_maintenance 100.00% 100.00% 0.00% 0.00% - - 10.501205 41.509081 9.819030 0.942027 9.403125 4.132490 1.239838 11.514120 0.0336 0.2859 0.1645 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 108: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 52.233314 52.233314 14.416774 1.618064 14.222627 3.165025 6.629123 2.725348 4.750974

Antenna 108: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 40.302564 10.701005 40.302564 11.117206 1.511384 5.907180 3.698566 2.501799 1.508797

Antenna 108: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape nan nan nan nan nan nan nan nan nan

Antenna 108: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 36.557096 9.058365 36.557096 9.505862 1.044969 7.924054 3.542085 1.677353 2.230131

Antenna 108: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 39.812838 9.930909 39.812838 10.077950 1.179237 7.675892 3.665477 3.617754 3.860061

Antenna 108: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance ee Shape nan nan nan inf inf nan nan nan nan

Antenna 108: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 43.608947 11.276149 43.608947 11.747069 1.268344 7.992844 2.900074 1.049351 4.659656

Antenna 108: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 42.566793 10.792701 42.566793 10.139645 1.300625 7.745029 3.525234 0.903349 5.625566

Antenna 108: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 44.051789 11.948281 44.051789 9.421633 1.051017 10.161838 5.622477 1.288991 2.157269

Antenna 108: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 49.358268 12.788336 49.358268 9.984651 1.181519 9.169805 4.327720 0.853244 7.546179

Antenna 108: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 39.984857 39.984857 10.338062 1.076982 9.776372 4.497040 9.064756 3.276152 0.828594

Antenna 108: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 41.529950 41.529950 10.099146 1.173350 8.701203 3.732639 7.989035 2.502827 0.481841

Antenna 108: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 48.562625 48.562625 12.166934 0.943454 10.087288 5.457371 10.763651 1.421041 0.735189

Antenna 108: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 40.613472 10.025405 40.613472 9.784654 1.126931 6.387764 3.097431 1.855988 2.352122

Antenna 108: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 49.291417 49.291417 12.539939 1.112814 10.715619 4.396200 9.361911 6.351336 5.862567

Antenna 108: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 45.913178 45.913178 11.525893 1.041365 9.929228 3.372369 7.215492 2.586017 2.105896

Antenna 108: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 44.958909 10.994953 44.958909 10.298232 1.156448 9.456326 6.923939 2.981381 2.082549

Antenna 108: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 43.357569 10.705542 43.357569 9.857574 1.021079 9.282236 4.850784 3.275835 4.561486

Antenna 108: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 32.619442 9.294123 32.619442 8.356958 1.460984 4.522754 2.706285 2.443456 1.732283

Antenna 108: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 39.578341 39.578341 9.975201 1.084610 10.507286 5.427580 10.447330 6.561492 0.917856

Antenna 108: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 36.467530 36.467530 9.777541 0.803848 9.441811 4.342896 9.027560 4.211356 5.275372

Antenna 108: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 40.495929 10.175792 40.495929 8.745526 0.903922 8.940644 4.277334 0.819913 11.842813

Antenna 108: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 41.850393 41.850393 10.274279 0.885222 9.498020 4.720671 9.330661 14.270272 0.813642

Antenna 108: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 41.863525 10.579775 41.863525 9.329338 1.070474 9.242066 7.425869 1.043007 13.869883

Antenna 108: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
108 N09 RF_maintenance nn Shape 41.509081 41.509081 10.501205 0.942027 9.819030 4.132490 9.403125 11.514120 1.239838
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